Thesis (M.S.)--Ohio University, March, 1994. / Title from PDF t.p.

This thesis proposes an algorithm and develops a program for fault detection and system restoration in medium voltage distribution systems. In Turkey, TUBITAK-UZAY developed distribution automation system including fault detection and service restoration functions for Bogazici Electricity Distribution Company. By the time, expanding of distribution system with nonstandardized infrastructure (for example more than one circuit breaker in the feeder, mesh and closed loop feeder structure), developed automation system have not properly worked under these unplanned situations. Taking into consideration of previously utilized TUBITAK Distribution Automation System (TUDOSIS), fault isolation algorithm is improved to cope with practical problems as non-standardized infrastructure and selectivity issue in protection system, and the proposed isolation algorithm is simulated. Further system restoration solution for mesh distribution systems is analyzed for distribution system in Turkey and expert system based algorithm is proposed.

Orientador: José Maria Campos dos Santos / Dissertação (mestrado profissional) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-18T21:55:11Z (GMT). No. of bitstreams: 1 Camargo_ThiagoAugustoBentodaSilva_M.pdf: 11218597 bytes, checksum: 9ad5907f28a4fff2ee79e0049c0e3460 (MD5) Previous issue date: 2011 / Resumo: Neste trabalho, foram feitas avaliações da utilização da transformada wavelet aplicada, principalmente, na identificação de falhas em rolamentos de esferas com contato angular. Como essa transformada pode ser comparada a transformada de Fourier, foi feito, primeiramente, um estudo comparativo entre a transformada wavelet contínua e a transformada de Fourier com sinais variantes no tempo. Posterior a essa avaliação, a transformada Wavelet discreta foi aplicada em diferentes métodos de identificação de presença de falhas em rolamentos como os métodos da porcentagem de energia, contagem de WZC (Wavelet Zero Crossing) e distancia euclidiana avaliados comparativamente entre sinais simulados de rolamento considerado bom e outro considerado ruim, para cada banda de freqüência. E, em seguida, a transformada wavelet contínua foi comparada através da avaliação dos resultados da identificação de origem de falhas pelo método do envelope, sendo utilizada como filtro em substituição ao filtro passa banda de Butterworth comumente utilizado. Os resultados mostraram que a transformada Wavelet consegue identificar a variação de freqüência em sinais variantes no tempo e a transformada de Fourier não. Os métodos que utilizaram a transformada wavelet discreta puderam fazer a identificação positiva da presença de falha em rolamentos, sendo que dois deles, método da energia e distancia euclidiana, apresentaram também robustez para identificação na presença de ruído branco nos sinais. Pela técnica do envelope, a transformada wavelet contínua, além de mostrar resultados equivalentes àqueles obtidos pela filtragem com filtro Butterworth, possibilitou identificações corretas de falhas em rolamentos em freqüências próximas à freqüência máxima de aquisição e também em janelas de inspeção com até 200 Hz de diferença entre a freqüência central da falha e da janela / Abstract: Hereby, the Wavelet transform was evaluated, mainly, being applied to angular contact ball bearings. As this transform can be comparable with the Fourier transform, a first comparative study was done using time variant signals in order to compare both transforms' performs. Afterwards, the discrete wavelet transform was applied on different fault presence identification methods as: WZC (Wavelet Zero Crossing) counting, energy percentage and Euclidian distance. On these cases, simulated bearing signals for good and bad condition were used. Furthermore, the continues wavelet transform was used as a substitute for the Butterworth filtering on the envelope method of fault origin identification. The results have shown that the wavelet transform can identify the frequency variation on time and the Fourier cannot. The method where the discrete wavelet transform was applied could successfully identify the fault presence on simulated signals, even when applied together with white noise. On the envelope method, the continuous wavelet transform had a equivalent performance as the Butterworth filtering and could also provide correct results even when the analyzed frequency was near the maximum acquisition frequency and also when the center frequency of the inspection window was up to 200 Hz higher, where the other filtering could not perform the same way / Mestrado / Dinâmica / Mestre em Engenharia Automobilistica

No / Fault management is one of the important management functions of a telecommunication network and mainly deals with fault monitoring and diagnosis. This paper applies reliability theories and methodologies for the fault management of an aeronautical communication system developed within the EU FP7 SANDRA project. The failure of the SANDRA terminal demonstrator is an undesirable event and the corresponding fault tree was built upon a reliability function analysis and was used to quickly monitor failures in the system. By using Monte Carlo simulations, the SANDRA demonstrator's reliability can be predicted and important components, which have major contributions to system failures, can be identified. The results can be used to improve the system reliability by adding parallel components in weak and important places.

Orientadores: João Mauricio Rosario, Paul Sas / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-07-21T14:19:07Z (GMT). No. of bitstreams: 1 Pereira_JoaoAntonio_D.pdf: 11639940 bytes, checksum: 8ae79402323dcf5b2975577c75bf8e14 (MD5) Previous issue date: 1996 / Resumo: Este trabalho propõe uma metodologia, baseada na utilização de técnicas de ajuste de modelos, para a localização de falhas em estruturas mecânicas. Inicialmente, é feito um levantamento das técnicas de comparação e ajuste de modelos bem como uma discussão detalhada das várias etapas envolvidas no processo tais como modelagem analítica, teste experimental, correlação, localização de erro e ajuste do modelo. Os problemas de incompatibilidade entre os modelos causados pela diferença entre o número de graus de liberdade do modelo analítico e do modelo experimental são resolvidos através da utilização de métodos de redução e um sistema de referência comum para os dois modelos, experimental e analítico. Diferentes métodos de comparação, correlação e ajuste são discutidos, enfatizando-se as vantagens dos métodos baseados em funções de resposta em freqüência para a localização de falha estrutural. A metodologia proposta assume que falhas estruturais provocam uma redução da rigidez e da massa (menos provável) do sistema levando assim à uma mudança das características dinâmicas da estrutura e consequentemente, uma deterioração da correlação inicial entre o modelo analítico e o modelo experimental. A análise desta perda de correlação dos modelos permite avaliar o estado de degradação da estrutura. Detectada uma alteração significativa do comportamento da mesma, o modelo analítico é atualizado em relação aos parâmetros físicos e/ou geométricos, e o novo modelo é comparado com os dados de referência buscando localizar a falha. Modelos numéricos simulados e dados experimentais foram utilizados na validação do método. Duas estruturas foram ensaiadas, uma parcialmente danificada e a outra com um membro complemente danificado. Os resultados obtidos em ambos os casos foram satisfatórios e bastante promissores. A metodologia localizou os componentes danificados das estruturas e permitiu uma estimativa da extensão dos danos das mesmas / Abstract: This work investigates the location and assessment of structural damage of fIexible structures by using a Non Destructive Evaluation (NDE) tool based on the model updating technique. First. A survey of the model test reconciliation and a positioning of its various phases such as analytical modelling, experimental test, model correlation. error localisation and model adjustment are presented. The problems of incompatibility of the models due to the difference of the number as well as the positions of the degrees of freedom from the analytical and the experimental models are solved by using methods of reduction, and a common system of reference for both models. Various methods of comparison, correlation and updating have been discussed. It is also highlighted the advantages of the use of FRF-based model updating for dartuigedetection purpose. The NDE approach assumes that structural damage provokes a reduction of the stiffness and mass (Iess expected) of the structure yielding a change of its structural dynamic behaviour and consequently, a deterioration of the original correlation between the analytical and experimental models. The loss of correlation of the models is used to evaluate the damage state of the structure. For those cases that is detected a significant change of the dynamic behaviour of the structure, the analytical model is updated, based on the measured damaged data, and the updated model is compared with the intact one in order to localize the damage. Therefore, for a success of the updating process, the comparison between the updated model and the original undamaged one can provide the changes of the structure, leading to the damage. The updating method incorporated in the approach is a FRF-base updating method that works at an element levei and does not interfere with the theory of finite element modeI. This feature allows to relate the changes of the updated model directly with the variation of the adjusted parameters of the elements. which makes the method very useful for damage detection, since the difference between the original and the updated model becomes physically interpretable. Numerical simulation has been used to validate the proposed method and also to investigate the influence of noise contamination on the FRF(s) and the influence of a reduced set of "measured" responses in the localization of the damage. Two experimental tests have been performed in order to demonstrate the capability and limitation of the procedure using real measured data. Initially, a partial damage of a frame structure was investigated and then a total damage of a member from a spatial beam like structure. The approach succeeded in both cases, and it was shown that the quality of the measurement data and the reliability of the initial finite e!ement mode! are important requirements for the success of the approach / Doutorado / Doutor em Engenharia Mecânica

Orientador: Jose Maria Campos dos Santos / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-13T03:19:31Z (GMT). No. of bitstreams: 1 Pereira_VilsonSouza_D.pdf: 15312128 bytes, checksum: 5088568f96c3f1f11b8524e51375c770 (MD5) Previous issue date: 2009 / Resumo: Neste trabalho, estudam-se os fenômenos de propagação de ondas elásticas em placas simples e acopladas e se propõe unia metodologia para análise do comportamento vibracional médio cm frequência-espaço com o objetivo de identificar como as vibrações se propagam através dessas estruturas em médias e altas freqüências. Para isso utilizou-se de métodos de energia originados da Análise de Fluxo de Energia (EFA) e que têm como variáveis primárias a densidade de energia e fluxo de energia. Duas formulações foram usadas para resolver as equações diferenciais de energia aproximada derivada du EFA: o Método dos Elementos Finitos de Energia (EFEM) e o Método do Elemento Espectral de Energia (ESEM). O Método do Elemento Espectral (SEM) foi uma outra formulação estudada para resolver as equações diferenciais de propagação de onda em placa fina, bem como para validar a metodologia proposta. Diferentes tipos de acoplamentos foram investigados e implementados tais como: placa-placa, placa com reforço e placa com dano. Para isso, desenvolveram-se relações de acoplamentos que descrevem essas descontinuidades estruturais. Uma investigação experimental do comportamento vibracional de uma placa simples e com reforço foi realizada para verificar os resultados do ESEM. De forma geral, observa-se que os resultados obtidos pelos modelos simulados apresentaram um comportamento semelhante aos resultados encontrados experimentalmente / Abstract: In this research, propagation phenomena of elastic waves to simple and coupled plates are investigated and a methodology, based on energy methods, is proposed to predict the space- and frequency-averaged vibrational response of these structures, at mid and high frequencies. These methods, originated from Energy Flow Analysis, use as primary variables the energy density and the energy flow, which are parameters to vibrational analysis. Two methodologies are used to solve approximated energy differential equations derived from EFA: Energy Finite Element Method (EFEM) and Energy Spectral Element Method (ESEM). Another formulation the Spectral Element Method (SEM), is used to solve differential wave equation of thin plates in terms of displacement, based on classical mechanics; moreover this method is applied to validate the proposed methodology. Different discontinued structures were investigated, such as plate-plate, reinforced plate and damaged plate. To this purpose, coupled relationships that represent these discontinuities are developed. An experimental investigation of vibrational response of a simple and reinforced plate was performed to verify the results of ESEM. The experimental results, calculated in terms of energy variables, to both analyzed structures, showed a good agreement with the simulated models / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

Modern digital energy meters are installed between the distribution network and customers. Network operators and customers can use those meters to monitor electrical parameters, i.e., voltages and currents and to calculate statistics such as RMS value, fundamental Fourier component, etc. Observation of distribution network impedance can reveal problems in the system, such as broken neutral conductors. This project proposes a loop-theory method using variables from smart meters to estimate the network impedance, therefore giving the possibility of conductor fault detection. Specifically, loop theory uses the distribution network terminal’s voltage and current measured by smart meters and selects cases where the load appears to have varied significantly, so that there is a change of current together with a resulting change of voltage. For selected cases, the methods calculate different loop impedance and finally address single conductor impedance by the least-squares method. The project validates the proposed method by simulation, and with recorded data from a real house with varied known neutral-conductor impedance. Based on that, this method’s limitation and possible improvement are discussed for further study. / Moderna digitala energimätare används mellan distributionsnätet och kunderna. Sådana mätare kan användas för att övervaka elektriska parametrar, dvs. spänningar och strömmar och beräkna statistik som RMS-värde, grundläggande Fourier-komponent etc. Observation av distributionsnätets impedans kan avslöja problem i systemet, såsom neutrala ledare med brott eller hög impedans (’nollfel’). Detta projekt föreslår en loopteorimetod med hjälp av variabler från smarta mätare för att uppskatta nätverksimpedansen, vilket ger möjlighet till detektering av ledningsfel. Specifikt använder loopteorin spänning och ström mätt med genom smarta mätare, och väljer fall där belastningen verkar ha varierat avsevärt så att det sker en förändring av strömmen tillsammans med en resulterande spänningsförändring. För valda fall beräknar metoderna impedanser i olika slingor av nätets ledare, och slutligen gör en estimering av impedansen hos enskilda ledare genom minstakvadratmetoden. Projektet validerar den föreslagna metoden genom simulering, och med inspelade data från ett riktigt hus med varierad känd neutral ledare impedans. Baserat på detta diskuteras denna metods begränsning och möjliga förbättring för vidare studier.

Orientador: Rubens Maciel Filho / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química / Made available in DSpace on 2018-08-22T08:44:14Z (GMT). No. of bitstreams: 1 Barbosa_AgremisGuinho_D.pdf: 4370227 bytes, checksum: 9fc9a5dfb766e6075fe58104c3c22087 (MD5) Previous issue date: 2008 / Resumo: O principal objetivo deste trabalho foi o desenvolvimento de um software para reconciliação de dados, detecção e identificação de erros grosseiros, estimativa de parâmetros e monitoramento da qualidade da informação em unidades industriais em estado estacionário e dinâmico. O desenvolvimento desse software focalizou atender aos critérios de modularidade, extensibilidade e facilidade de uso. A reconciliação de dados é um procedimento de tratamento de medidas em plantas de processos necessário devido ao fato da inexorável presença de erros aleatórios de pequena magnitude associados aos valores obtidos dos equipamentos de medição. Além dos erros aleatórios, por vezes os dados estão associados a erros de maior magnitude e que constituem uma tendência, ou viés. Erros desta natureza podem ser qualificados e quantificados por técnicas de detecção de erros grosseiros. É importante para aplicação de subrotinas de otimização que os dados sejam confiáveis e livres de erros tanto quanto possível. A tarefa da remoção destes erros através de modelos previamente conhecidos (reconciliação de dados) não é trivial, já sendo estudada no campo da engenharia química nos últimos 40 anos e apresenta uma crescente quantidade de trabalhos publicados. Contudo, uma parte destes trabalhos é voltada para aplicação da reconciliação sobre equipamentos isolados, como tanques, reatores e colunas de destilação, ou pequenos conjuntos destes equipamentos e não são muitos os trabalhos que utilizam dados reais de operação. Isto pode ser atribuído à dimensão do trabalho computacional associado ao grande número de variáveis. O que se propõe neste trabalho é tomar partido da crescente capacidade computacional e das modernas ferramentas de desenvolvimento, provendo uma aplicação na qual seja facilitada a tarefa de descrever sistemas de maior dimensão, para estimar dados de qualidade superior, em tempo hábil, para sistemas de controle e otimização. É importante frisar que a reconciliação de dados e a detecção de erros grosseiros são fundamentais para a confiabilidade de resultados de subrotinas de otimização e controle supervisório e também pode ser utilizada para a reconstrução de estados do processo / Abstract: The main goal of this work was the development of software for data reconciliation, gross errors detection and identification, data reconciliation, parameter estimation, and information quality monitoring in industrial units under steady state and dynamic operation. The development of this software was focused on meeting the criteria of modularity, extensibility, and user friendliness. Data reconciliation is a procedure for measurement data treatment in process plants, which is necessary due the fact of the inexorable presence of random, small magnitude errors associated to the values obtained from measurement devices. In addition to the random errors, sometimes data are associated to major magnitude errors that lead to a trend or bias. Errors of this nature can be qualified and quantified through gross errors detection techniques. It is important for optimization routines that data are reliable and error free as much as possible. The task of removal of these errors using previously known models (data reconciliation) is not trivial, and has been studied for the last 40 years in the field of chemical engineering, showing an increasing amount of published works. However, part of these works is devoted to applying data reconciliation over single equipment, such as tanks, reactors, distillation columns, or small sets of these equipments. Furthermore, not much of this published work relies on real operation data. This can be regarded to the dimension of computational work associated to the great number of variables. This work proposes to take advantage of increasing computational capacity and modern development tools to provide an application in which the task of higher dimension systems description is accomplished with ease in order to produce data estimates of superior quality, in a suitable time frame, to control and optimization systems. It is worthwhile mentioning that data reconciliation and gross error detection are fundamental for reliability of the results from supervisory control and optimization routines, and can be used also to process state reconstruction / Doutorado / Desenvolvimento de Processos Químicos / Doutor em Engenharia Química

No description available.

Electric power distribution network is an important part of electrical power systems for delivering electricity to consumers. Electric power utilities worldwide are increasingly adopting the computer aided monitoring, control and management of electric power distribution systems to provide better services to the electrical consumers. Therefore, research and development activities worldwide are being carried out to automate the electric power distribution system. The power distribution system consists of a three-phase source supplying power through single-, two-, or three-phase distribution lines, switches, and transformers to a set of buses with a given load demand. In addition, unlike transmission systems, single-, two-, and three-phase sections exist in the network and single-, two-, and three-phase loads exist in the distribution networks. Further, most distribution systems are overhead systems, which are susceptible to faults caused by a variety of situations such as adverse weather conditions, equipment failure, traffic accidents, etc. When a fault occurs on a distribution line, it is very important for the utility to identify the fault location as quickly as possible for improving the service reliability. Hence, one of the crucial blocks in the operation of distribution system is that of fault detection and it’s location. The achievement of this objective depends on the success of the distribution automation system. The distribution automation system should be implemented quickly and accurately in order to isolate those affected branches from the healthy parts and to take alternative measures to restore normal power supply. Fault location in the distribution system is a difficult task due to its high complexity and difficulty caused by unique characteristics of the distribution system. These unique characteristics are discussed in the present work. In recent years, some techniques have been discussed for the location of faults, particularly in radial distribution systems. These methods use various algorithmic approaches, where the fault location is iteratively calculated by updating the fault current. Heuristic and Expert System approaches for locating fault in distribution system are also proposed which uses more measurements. Measurements are assumed to be available at the sending end of the faulty line segment, which are not true in reality as the measurements are only available at the substation and at limited nodes of the distribution networks through the use of remote terminal units. The emerging techniques of Artificial Intelligence (AI) can be a solution to this problem. Among the various AI based techniques like Expert systems, Fuzzy Set and ANN systems, the ANN approach for fault location is found to be encouraging. In this thesis, an ANN approaches with limited measurements are used to locate fault in long distribution networks with laterals. Initially the distribution system modeling (using actual a-b-c phase representation) for three-, two-, and single-phase laterals, three-, two-, and single- phase loads are described. Also an efficient three-phase load flow and short circuit analysis with loads are described which is used to simulate all types of fault conditions on distribution systems. In this work, function approximation (FA) is the main technique used and the classification techniques take a major supportive role to the FA problem. Fault location in distribution systems is explained as a FA problem, which is difficult to solve due to the various practical constraints particular to distribution systems. Incorporating classification techniques reduce this FA problem to simpler ones. The function that is approximated is the relation between the three-phase voltage and current measurements at the substation and at selected number of buses (inputs), and the line impedance of the fault points from the substation (outputs). This function is approximated by feed forward neural network (FFNN). Similarly for solving the classification problems such as fault type classification and source short circuit level classification, Radial Basis Probabilistic Neural Network (RBPNN) has been employed. The work presented in this thesis is the combinational use of FFNN and RBPNN for estimating the fault location. Levenberg Marquardt learning method, which is robust and fast, is used for training FFNN. A typical unbalanced 11-node test system, an IEEE 34 nodes test system and a practical 69- bus long distribution systems with different configurations are considered for the study. The results show that the proposed approaches of fault location gives accurate results in terms of estimated fault location. Practical situations in distribution systems such as unbalanced loading, three-, two-, and single- phase laterals, limited measurements available, all types of faults, a wide range of varying source short circuit levels, varying loading conditions, long feeders with multiple laterals and different network configurations are considered for the study. The result shows the feasibility of applying the proposed method in practical distribution system fault diagnosis.